Peter Speltz
- Molecular Biology
- Artificial Intelligence top 10%
- Health Information Management top 2%
- Genetics
- Public Health, Environmental and Occupational Health
- Co-authors
- Joshua C. DennyJyotishman PathakJennifer A. PachecoLuke V. RasmussenDan M. RodenMelissa BasfordPaul A. HarrisOmri Gottesman
- Topics
- Biomedical Text Mining and Ontologies (8 papers)Scientific Computing and Data Management (4 papers)Electronic Health Records Systems (3 papers)
- Journals
- Journal of the American Medical Informatics AssociationJournal of Biomedical InformaticsPharmacogenomics
- Partner nations
- United States
In The Last Decade
Peter Speltz
11 papers receiving 394 citations
Peers
Comparison fields: 5 of 73
- Molecular Biology 157
- Artificial Intelligence 155
- Health Information Management 100
- Genetics 64
- Public Health, Environmental and Occupational Health 56
Countries citing papers authored by Peter Speltz
This map shows the geographic impact of Peter Speltz's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Peter Speltz with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Peter Speltz more than expected).
Fields of papers citing papers by Peter Speltz
This network shows the impact of papers produced by Peter Speltz. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Peter Speltz. The network helps show where Peter Speltz may publish in the future.
Co-authorship network of co-authors of Peter Speltz
This figure shows the co-authorship network connecting the top 25 collaborators of Peter Speltz. A scholar is included among the top collaborators of Peter Speltz based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Peter Speltz. Peter Speltz is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 6 | |
| 2 | 2 | |
| 3 | 238 | |
| 4 | 28 | |
| 5 | Harmonization of Quality Data Model with HL7 FHIR to Support EHR-driven Phenotype Authoring and Execution: A Pilot Study. | 2 |
| 6 | A Prototype for Executable and Portable Electronic Clinical Quality Measures Using the KNIME Analytics Platform. | 7 |
| 7 | A Modular Architecture for Electronic Health Record-Driven Phenotyping. | 16 |
| 8 | 26 | |
| 9 | Evaluation of Existing Phenotype Authoring Tools for Clinical Research. | 1 |
| 10 | 70 | |
| 11 | Comparing content coverage in medical curriculum to trainee-authored clinical notes. | 2 |
About Peter Speltz
Peter Speltz is a scholar working on Family Practice, Health Information Management and Information Systems and Management, having authored 11 papers that have together received 398 indexed citations. Recurring topics across this work include Biomedical Text Mining and Ontologies (8 papers), Scientific Computing and Data Management (4 papers) and Electronic Health Records Systems (3 papers). The work is most often cited by research in Health Information Management (100 citations), Health Informatics (27 citations) and Computational Mathematics (4 citations). Peter Speltz has collaborated with scholars based in United States. Frequent co-authors include Joshua C. Denny, Jyotishman Pathak, Jennifer A. Pacheco, Luke V. Rasmussen, Dan M. Roden, Melissa Basford, Paul A. Harris, Omri Gottesman, Jonathan L. Haines and Peggy Peissig. Their work appears in journals such as Journal of the American Medical Informatics Association, Journal of Biomedical Informatics and Pharmacogenomics.
Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.